PA: INNOVATIVE TOXICOLOGY
MODELS FOR DRUG EVALUATION
RFA: NIDDK
BIOTECHNOLOGY CENTERS
U19: Toxicogenomics Research Consortium
Microarrays and Toxicology: The Advent
of Toxicogenomics(index reference)
Forward References (to ibid.)
Abstracts (to ibid.)
Other References
Agreements to Participate
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insults |
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genomics |
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infection |
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evaluation of potential drug candidates |
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causes of hepatotoxicity |
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changes during development of disease or therapeutic agent treatment |
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compounds |
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incorporates the application of pharmacogenomics principles to issues of predictive toxicity. |
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computational biology tools |
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in response to beta-naphthoflavone (beta-NF) = Upregulation of cytochrome P4501a1 |
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drug safety |
National Cancer Institute
Letter of Intent Receipt Dates: December 7, 2000 and October 10, 2001
Application Receipt Dates: January 11, 2001 and November 14, 2001
The overall objective of this PA is to provide a flexible funding mechanism to support the research activities required to develop and validate innovative "toxicogenomic" assays.
New technology to improve approaches that define new (cancer/AIDS) drug toxicity at the molecular level are emerging, but as yet none has been validated and accepted for common use. For example, bacterial strains and transgenic mice have been engineered to detect mutational activities of agents. "Toxicogenomics", e.g.,analysis of the gene transcription profile in a cell or organ following toxic agent administration [Molecular Carcinogenesis 24:153-159 (1999)] is under development using a variety of approaches, including DNA arrays. Data analysis software programs are being written to predict toxicological endpoints. Individually, these activities may not be sufficient, but they may be highly valuable when combined with other approaches to develop a total toxicological profile of specific organ toxicity and molecular mechanisms responsible for this toxicity.
Objectives and Scope
The goal of this PA is the discovery, development
and validation of new assays and procedures to determine quickly and cheaply
toxicological profiles of cancer drugs. It is expected that a molecular
definition of toxicity in the affected organ, tissue or cell would be a
component of the procedure {Clinical connections at AMC - Drs. Drusano,
Ledger, and/or Spivack:
p53 probe array design}. Approaches for new toxicology
assays in response to this initiative are broad and are determined by the
creativity of the applicant {Drs. Kaminsky, Ding: CYP450
probe array design}. Genetically modified animals or
cell lines {Dr. Flaherty}, various non-mammalian organisms
{Dr. Keithly}, in vitro assays utilizing primary mammalian
cells, tissue slices, isolated organs, sub-cellular fractions or purified
enzymes could be utilized for the model {Dr. Schneider}.
Computer modeling utilizing existing biological and toxicological data
bases would be appropriate{Dr. Reilly}. Genomic and proteomic
technology could be exploited to profile total gene activity or protein
expression and thereby establish molecular correlations with specific toxicities{Affymetrix
Core}. Molecular endpoints to evaluate toxicity and high throughput
toxicity screening could be used to help decide which agent of a chemical
series of drug analogues should be pursued, to allow exploration of toxicity
at an earlier stage in drug development {wouldn't this involve confirming
the developed molecular endpoint in an animal model before moving to humans?},
or to define the toxicity profile of agents selected for clinical trial.
Mechanism of Support
Under this PA, applicants can submit either an
R21, a combined R21/R33, or an R33 application alone if feasibility can
be documented, as described in the APPLICATION PROCEDURES section of this
PA. The total project period for an application submitted in response to
this PA may not exceed the following duration: R21, 2 years; R33, 3 years;
combined R21/R33 application, 4 years. In the combined application the
R21 phase cannot extend beyond 2 years. The R21 phase, either as
a single application or as part of a combined R21/R33 application, may
not exceed $100,000 direct costs per year except to accommodate Facility
and Administrative (F&A;) costs to subcontracts to the projects. Although
the R33 application has no official budgetary limit, applications requesting
in excess of $500,000 dollars direct costs in any single year of the grant
period require prior approval before submission.
Back to Contents
Release Date: October 30, 2000
RFA: DK 01 019
National Institute of Diabetes and Digestive and
Kidney Diseases
Letter of Intent Receipt Date: December 22, 2000
Application Receipt Date: January 19, 2001
This RFA is intended to support the cost effective introduction of techniques to measure patterns of gene expression in specific tissues of interest to the NIDDK supported investigators. This RFA will allow the formation of support facilities that may include, but are not limited to:
1. cDNA Microarrays; 2. Oligonucleotide Chips.
Creation and maintenance of these technologies may require the collaboration of investigators with expertise in many fields, such as molecular biology(), robotics(), bioinformatics(Dr. Reilly), genomic (Dr. Lawrence), and statistics (Dr. Reilly). In addition, key aspects of infrastructure may also be supported and might include the development and maintenance of appropriate databases and specialized equipment. It is important to emphasize that there are a variety of approaches to genome wide expression analysis. Therefore, a given strategy must be rigorously justified and must demonstrate that all key personnel are involved in the formulation of the rationale and approach. Applicants will be required to describe projects that will benefit from these technologies.
MECHANISM OF SUPPORT
This RFA will use the NIH grant in aid resource
related mechanism grant (R24) award. Except as otherwise stated in this
announcement, awards will be administered as stated in the NIH Grants Policy
Statement. The total requested project period for an application submitted
in response to this RFA may not exceed three years. The maximum request
is limited to $350,000 of direct costs for each budget year. For FY 2001,
$3 million will be committed to fund applications submitted in response
to this RFA. It is anticipated that about six Biotechnology Centers will
be funded; however, this funding level is dependent upon the receipt of
a sufficient number of applications of high scientific merit.
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Primary Sponsor: National Institute of Environmental Health Sciences
Deadline: 2/15/2001; 3/15/2001
RFA: ES-01-002
Letter of Intent Receipt Date: February 15, 2001 Application Receipt Date: March 15, 2001
The Toxicogenomics Research Consortium (TRC) program is to establish a consortium of five or six Cooperative Research Members (CRMs), each with an established research infrastructure and research excellence in gene expression profiling technologies, that will conduct research within the mission responsibilities including both basic and toxicological activities of the NIEHS as requested in this RFA. The CRMs, operating within the Consortium program will address three main goals:
MECHANISM OF SUPPORT
A U19 mechanism provides support for both research project components
and core facilities. A cooperative agreement is an assistance
mechanism (rather than in acquisition mechanism) in which substantial NIH
scientific or programmatic involvement with the awardee is anticipated
during the performance of the activity. Under the cooperative
agreement, the NIEHS=s role is to support and/or stimulate the recipient's
activity by working jointly with the award recipient as a partner, but
it is not to assume direction, prime responsibility, or a dominant role
in the activity.
Back to Contents
Microarrays and Toxicology: The Advent of Toxicogenomics
Emile F. Nuwaysir, Michael Bittner, Jeffrey
Trent, J. Carl Barrett, and Cynthia A. Afshari.
MOLECULAR CARCINOGENESIS 24:153 159 (1999)
| Inactivation
of the DNA-Repair Gene MGMT and the Clinical Response of Gliomas to Alkylating
Agents,
(N Engl J Med 2000;343:1350-4.) Manel Esteller, Jesus Garcia-Foncillas, Esther Andion, Steven N. Goodman, Oscar F. Hidalgo, Vicente Vanaclocha, Stephen B. Baylin, James G. Herman Abstract
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| Related Editorial
Traditionally, cancer treatments have been selected on the basis of tumor type, pathological features, clinical stage, the patient's age and performance status, and other nonmolecular considerations. We have generally accepted with a certain fatalism that some patients pigeonholed into a given category will have a response to a particular therapy, whereas others will not. The difference is often viewed as a matter of luck, like the result of a coin toss, but in fact, treatment response can be predicted in some cases, whereas it is close to impossible to predict the results of a coin toss. The field of pharmacogenomics, through the study of large numbers of genes that influence drug activity, toxicity, and metabolism, provides the opportunity to tailor drug treatments and to eliminate many of the uncertainties of current therapy for cancer. Strong support for this concept is provided by the study of genetic polymorphisms that influence drug metabolism. (1) CYP2D6, for example, affects the metabolism of a wide range of agents, including beta-blockers, antidepressants, antipsychotics, and opioids. Dihydropyrimidine dehydrogenase influences the metabolism, and therefore the neurotoxicity, of fluorouracil. DNA-sequence variants may also directly influence the toxic side effects of a drug or its ability to interact with its target. In this issue of the Journal, Esteller and colleagues (2) provide clinical evidence of an intriguingly different sort of mechanism -- an epigenetic one that does not involve any change in DNA sequence -- to explain the resistance of some gliomas to nitrosourea alkylating agents. Carmustine (BCNU) and other nitrosoureas kill by alkylating the O6 position of guanine and thereby cross-linking adjacent strands of DNA. Formation of these cross-links can be prevented by the DNA-repair enzyme O6-methylguanine-DNA methyltransferase (MGMT), which rapidly reverses the alkylation. Wide variations in the expression of MGMT are found within and among tumor types. In particular, about 30 percent of gliomas lack MGMT. Although the literature on this subject is complex, a lack of MGMT appears to correlate with sensitivity to carmustine. Mutations in the DNA sequence of MGMT are unusual and cannot be invoked to explain the variation in levels of expression. So what is the mechanism? It has been proposed that methylation of the MGMT promoter region, with consequent transcriptional silencing of the gene, may account for this variation. (3) DNA methylation of normally unmethylated CpG (cytidine-phosphate-guanidine) islands in the promoter regions of genes for tumor suppressors, DNA-repair enzymes, receptors, and cell-cycle proteins can silence those genes in cancer cells and thus influence tumor evolution. Using a methylation-specific form of the polymerase chain reaction, (4) Esteller et al. (2) studied methylation of the MGMT promoter in 47 consecutive newlydiagnosed grade III and IV gliomas and found a striking relation to the response to treatment with carmustine. Twelve of 19 patients with methylated promoters in their tumors had a partial or complete response to treatment, whereas only 1 of 28 patients with an unmethylated promoter had a response (P<0.001). Overall survival and time to progression were also longer in patients whose tumors had methylated promoters. (2) These findings suggested that methylation of the MGMT promoter could be used to predict responses to treatment with carmustine. Further clinical studies will be necessary, of course, to validate these impressive first results, and it would be interesting to verify directly that methylation of the MGMT promoter in these tumors correlates strongly with MGMT expression and activity. But the implications of the study, if its results can be replicated, are clear: carmustine therapy might be reserved for patients whose gliomas have methylated MGMT promoters, and the response to carmustine might be increased by agents such as O6-benzylguanine that inhibit MGMT activity. A very simple calculation indicates the potential power of such therapeutic markers. For the 47 patients in the study by Esteller et al., the overall tumor response rate was 27.7 percent. Given that response rate, if this had been a phase 1 trial of a new drug, 10 patients taking an effective dose would have been required to produce a 95 percent chance of at least one response. In contrast, if only those with methylated promoters (with the observed 63.2 percent response rate) had been admitted to the trial, only three patients would have been needed to achieve similar certainty of seeing at least one response. More important for clinical practice, patients with unmethylated MGMT promoter regions in their tumors could be spared the considerable toxicity of carmustine and could instead be given an agent more likely to be effective against the tumor. Pharmacogenomic studies will inevitably produce benefits such as these for both clinical research and standard practice. From the perspective of the pharmaceutical industry, they have the potential disadvantage of dividing the market for a successful drug, but their larger potential advantages include the discovery of better drugs, elimination of poor candidate drugs early in the development process, and dramatic decreases in the size and expense of clinical trials. The study by Esteller and colleagues provides a case in point. It presents clinical correlations with respect to a particular promoter and a particular class of drugs. But it immediately raises broader questions. The nitrosoureas have activity in tumors other than gliomas, including some lymphomas, cancers of the gastrointestinal tract, and melanomas. Will MGMT-promoter methylation serve to identify patients with those cancers who might benefit from therapy with nitrosoureas? More generally, how often will epigenetic methylation of CpG islands in promoters of other genes prove useful for the selection of treatments beyond the nitrosoureas? To address the latter question, various methods are being developed to scan large numbers of promoters for differences in methylation. (5) Thus it seems likely that progress in this field will require a survey of many genes. Such comprehensive approaches to biology can be characterized as "omic" research (6) -- that is, research in which one generates large resources of information on biologic molecules in aggregate without necessarily knowing in advance which pieces of information and which correlations will prove most important. (7) "Omic" research is hypothesis-driven, but the hypothesis relates to information and its usefulness, rather than to particular molecules or processes. "Omics" began with genomics and the Human Genome Project. Then, as coined by various researchers, there came proteomics, kinomics (for the kinases in aggregate), CHOmics (for the carbohydrates), metabolomics, immunomics, toxicomics, and clinomics -- as well as compound forms, such as functional genomics, structural genomics, and pharmacogenomics. In view of the study by Esteller et al., (2) and as we search for other clinically relevant instances in which promoter methylation affects therapy, can "pharmacomethylomics" be far behind? John N. Weinstein,
M.D., Ph.D.
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